In [1]} the idea of learning a parametric function is employed for a set of typical continuous control RL problem like Ant, Walker2D, HumanoidStandup and Humanoid. These environments are implemented in OpenAI Gym [2]}. For each problem, a particular parametric reward function is defined and the same algorithm is used for learning both the parameters of reward and policy network. Actor-critic algorithms including Proximal Policy Optimization [3]} and Soft Actor Critic [4]} are used with parametric reward function and the method outperforms the same algorithms without parametric reward on the aforementioned tasks.
